Digital Commons Network^™

Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Mohammed Rafeeq Khan

Graduate Theses and Dissertations (2019 - present)

A three-dimensional neuromorphic (3D) computing architecture based on environmentally sustainable natural organic honey memristors is proposed in this thesis. A set of comprehensive and experimental results indicate that the proposed systems exhibit remarkable inference accuracy, consistently surpassing the 90% threshold, even with different challenges such as device variations and nonlinearity. This study also considers four different conductance drift situations, the effects of analog-to-digital converter (ADC) quantization, and multiple algorithms, such as VGG8 and DenseNet-40. The deliverable of this thesis will test the stability of the proposed systems and explore their potential applications and scalability in real-world situations.

A Graph Motif Adversarial Attack For Fault Detection In Power Distribution Systems, Dibaloke Chanda, Nasim Yahyasoltani

Computer Science Faculty Research and Publications

Fault detection is an integral part of the protection system in a power distribution network. Due to advanced computational capabilities, deep learning-based algorithms can significantly outperform traditional methods. However, these deep learning models are prone to adversarial attacks which are not well-addressed as traditional cyber attacks in distribution systems. More specifically, to capture the structure of distribution systems, graph neural networks (GNNs) are employed. Leveraging the backdoor attack model, we propose a novel graph-based adversarial attack algorithm for fault detection in power systems. It is further shown that the adaptable structure of GNN can make them vulnerable to adversarial attacks …

Equitable Community-Based Participatory Research Engagement With Communities Of Color Drives All Of Us Wisconsin Genomic Research Priorities, Sheikh Iqbal Ahamed, Praveen Madiraju

Computer Science Faculty Research and Publications

Objective

The NIH All of Us Research Program aims to advance personalized medicine by not only linking patient records, surveys, and genomic data but also engaging with participants, particularly from groups traditionally underrepresented in biomedical research (UBR). This study details how the dialogue between scientists and community members, including many from communities of color, shaped local research priorities.

Materials and Methods

We recruited area quantitative, basic, and clinical scientists as well as community members from our Community and Participant Advisory Boards with a predetermined interest in All of Us research as members of a Special Interest Group (SIG). An expert …

Artificial Intelligence Uncertainty Quantification In Radiotherapy Applications – A Scoping Review, Kareem A Wahid, Zaphanlene Y Kaffey, David P Farris, Laia Humbert-Vidan, Amy C Moreno, Mathis Rasmussen, Jintao Ren, Mohamed A Naser, Tucker J Netherton, Stine Korreman, Guha Balakrishnan, Clifton D Fuller, David Fuentes, Michael J Dohopolski

Faculty, Staff and Student Publications

Background/purpose: The use of artificial intelligence (AI) in radiotherapy (RT) is expanding rapidly. However, there exists a notable lack of clinician trust in AI models, underscoring the need for effective uncertainty quantification (UQ) methods. The purpose of this study was to scope existing literature related to UQ in RT, identify areas of improvement, and determine future directions.

Methods: We followed the PRISMA-ScR scoping review reporting guidelines. We utilized the population (human cancer patients), concept (utilization of AI UQ), context (radiotherapy applications) framework to structure our search and screening process. We conducted a systematic search spanning seven databases, supplemented by manual …

Real-Time Network Simulations For Ml/Dl Ddos Detection Using Docker, Luis D. Garcia

Master's Theses

As the integration of artificial intelligence (AI) within cybersecurity continues to

grow, machine learning (ML) and deep learning (DL) models are increasingly used to

detect cyber attacks. However, these models are rarely evaluated in real-time attack

scenarios to see how subtle changes from the real networking environment can affect

their predictions. To address this issue, we propose a scalable, platform-independent

Docker testbed specifically designed for simulating real-time Distributed Denial of

Service (DDoS) attack scenarios that allows researchers to deploy and evaluate their

pre-trained, ML and DL detection models. Our framework is simple to configure

and can run across Intel and …

The Application Of Generative Ai For Sketch-To-Image Conversion, Jeremy J. Kozlowski

Master's Theses

Sketches have historically been the primary way to identify individuals when images are unavailable. Most commonly, this appears in a police investigation, where the police release a sketch to the public in an attempt to find a suspect. However, sketches occasionally do not provide much detail due to the limitations of both the witness and the artist. A poor sketch greatly hinders the public’s ability to identify someone, decreasing the chances they will be found. To improve upon this inefficient way of identifying individuals, we propose a new pipeline that leverages deep generative artificial intelligence models to create detailed images …

Peer Collaborative Networks In Undergraduate Computing Classrooms, Noah T. Ravetch

Master's Theses

Peers are an invaluable resource for students at undergraduate universities. Many factors can impact how students form connections, some of which are tied to the students’ identities. While social networks have been studied in the context of universities, little research has been done specifically about peer collaboration and even less in the context of computer science classes. Our research aims to gain an understanding of how peer networks form in computing classes and the effect of being involved in one on students’ academic performances. We collected survey data (n = 139) about students’ peer collaborative behaviors in computer science classes. …

Finite Element Analysis And Verification Of Transverse Mechanical Properties Of Generally Cylindrical Orthotropic Constitutive Modeling Of 3-Phase Nanocomposite Unit Cell, Christopher J. Hawkins

Master's Theses

Fiber-reinforced composites are increasingly popular due to their specific strength and stiffness, making them ideal for high-performance applications. However, these materials primarily exhibit superior properties in-plane, while their out-of-plane characteristics remain comparatively weaker. Previous research has shown that the most effective method to enhance out-of-plane properties involves the incorporation of carbon nanotubes. Experimental tests have demonstrated significant improvements in properties such as tension, flexural, short beam shear, and fracture toughness. Alongside these experimental studies, analytical equations have been developed to predict the behavior of these composites under various loading conditions, including tension, bending, shear, and fracture. Existing models primarily address …

Joseph Moxon: Fueled By Science, Extinguished By Class. How A Forgotten Middle-Classed Early Modern English Puritan Printer Mathematician And Globe-Maker Helped Forge The Scientific Revolution And Democratize Knowledge Among The Trades, Kenneth L. Macro Jr.

Master's Theses

Joseph Moxon, raised within the trades, elevated into the middle-class, was an inducted Fellow of the Royal Society, Hydrographer to the King’s Most Excellent Majesty, Printer, Author, Translator, Maker of Globes and of Spheres, Maker of Maps and of Mathematical Instruments, Engraver, and Entrepreneur. Moxon was the quintessential Renaissance Man. A tradesman living in a time of great scientific intrigue and discovery, Moxon, acknowledged by few mid-seventeenth century historians, rightfully contributed his scientific discoveries—in the forms of tutorials and manuals written for the common man—as a testimony to all printers who have helped in the progression of the Scientific Revolution. …

Ultrasound Denoising And Speckle Reduction Using Artificial Neural Networks, Mark Atttaalla

Master's Theses

This paper focuses on improving speckle reduction and denoising performance in ultrasound images by leveraging neural networks. A dataset of simulated ultrasound images was created using Field-II simulation software based on CT scan images, to create clean and noisy image pairs. Various Convolutional Neural Network models based on U-Net and generative adversarial networks were developed and tested. Peak Signal-to-Noise-Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) were used as metrics along with qualitative assessment. Results show that our tuned U-Net generator network outperformed traditional filtering such as Lee and BM3D.

Qualitative Insights Into School Improvement Practices: Stakeholder Perceptions In Ghanaian Junior High Schools, Mark Quansah Dr., Emmanuel Erastus Yamoah Dr

The Qualitative Report

This study aims to explore diverse perspectives on strategies for enhancing academic performance in Ghanaian Junior High Schools (JHSs). Recognizing the importance of context and stakeholder input, the research investigates the perceptions of teachers, headteachers, and school improvement support officers (SISOs) regarding effective school improvement practices. The study examined two Ghanaian districts using a qualitative case study design within an interpretive paradigm. Purposive sampling with maximum variance was used to target 20 participants, including 10 teachers, five headteachers, and five SISOs. Semi-structured interviews were used for data gathering, and the results were subjected to thematic analysis to find trends and …

Exploring Secure Methods For Ensuring Data Integrity: A Theoretical Analysis Of Cryptographic And Detection Techniques, Haryam Garcia Martinez

Electronic Theses, Projects, and Dissertations

This study investigates cryptographic methods to ensure data integrity within cloud environments, with a particular focus on comparing the security, performance, and efficiency of MD5 and SHA-256 hash algorithms. Data integrity is critical for protecting sensitive information, especially in sectors like healthcare, where cloud storage solutions are increasingly prevalent. Through a theoretical analysis, the study evaluates the advantages and limitations of MD5 and SHA-256, emphasizing SHA-256’s stronger security capabilities in preventing collision attacks compared to MD5, albeit with higher resource consumption.

The literature review draws from recent advancements in cryptography, blockchain, and artificial intelligence (AI) technologies, presenting a comprehensive view …

The Practical Adoption And Application Of Blockchain Technology Within The Beverage Industry, Alexander Adams Jr

Electronic Theses, Projects, and Dissertations

Abstract

The beverage industry is facing heightened scrutiny as the demand for transparency and accountability reaches new heights. In the age of information technology, companies must prioritize enhanced traceability to ensure product safety, comply with government regulations, maintain customer trust, and protect brand integrity. This thesis explores the potential of blockchain technology as a solution to these challenges, focusing on its ability to decentralize data, improve traceability, and expedite response times during safety recalls. The research provides an overview of the evolution of food safety regulations, beginning with the first establishment by Upland Sinclair, and examines current traceability practices and …

Exploring The Impact Of Leaders’ Emotional Intelligence On Employee Retention And Job Satisfaction: An Employee-Centric Perspective, Stacia Mccambridge

Electronic Theses, Projects, and Dissertations

Employee retention and job satisfaction are crucial for the success of higher education institutions, as turnover incurs high costs and disrupts operations. This qualitative phenomenological study explored how leaders’ emotional intelligence, as defined by self-awareness, self-management, social awareness, and relationship management emotional intelligence, impacts employee satisfaction and retention in university settings in Southern California. The theoretical framework used for this study was the emotional intelligence theoretical framework of Goleman et al. (2002), which includes self-awareness, self-management, social awareness, and relationship management competencies to conduct surveys and interviews. The two research questions that guided this study of how employees described, based …

Fortifying Ai-Iot Food Supply Chains: Addressing Third-Party Cybersecurity Vulnerabilities, Ashwin Chudasama

Electronic Theses, Projects, and Dissertations

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) technologies within food supply chains has led to significant operational efficiencies but has also introduced cybersecurity vulnerabilities, especially from third-party vendors supplying critical software and hardware. This study explores these vulnerabilities and evaluates multi-layered defense strategies to mitigate the cybersecurity risks they introduce. The research questions guiding this study are: (Q1) How do third-party vendors contribute to cybersecurity vulnerabilities within AI-IoT systems in the food industry? (Q2) How can multi-layered defense strategies effectively mitigate the cybersecurity risks introduced by these vendors?

Using a systematic literature review (SLR) approach …

The Effects Of Covid-19 Lockdowns On Cybersecurity, Natalie Sanders

Electronic Theses, Projects, and Dissertations

The COVID-19 pandemic and subsequent lockdowns forced many Americans to quickly adapt to working from home, many of which had never done so in the past. In addition, organizations were forced to modify security policies and protocols to allow for remote access to sensitive information. The rapid change in security policies as well as the sudden growth of remote access during the pandemic presented a broader landscape for cyber criminals to attack. In this report, we review the number and type of cyberattacks reported from two (2) years before the pandemic through two (2) years after (1998 through 2023), to …

The Disordered Negatively Charged C-Terminus Of The Large Hect E3 Ubiquitin Ligase Herc2 Provides Structural And Thermal Stability To The Hect C-Lobe, Kelly L. Waters, Kayla J. Rich, Noah D. Schwaegerle, Tianyi Yang, Shuanghong Huo, Donald E. Spratt

Chemistry

Homologous to the C-terminus of E6AP (HECT) and RCC1-like domain (RLD)-containing protein 2 (HERC2) is a large, 528 kDa E3 ubiquitin ligase that is associated with cancer, oculocutaneous albanism type 2, Prader-Willi syndrome, and other neurological diseases. HERC2 has been found to contribute to double-stranded DNA break repairs, tumor suppression, maintaining centrosome architecture, and ubiquitylation. The C-terminal portion of the HECT domain (C-lobe) of HERC2 is responsible for transferring ubiquitin to a substrate but the precise function of the other eight domains in HERC2 are unknown. Interestingly, HERC2 contains a unique and negatively charged C-terminal …

Pixels Of Passion: The Revolutionary Impact Of Indie Games, Sharanya Udupa

ART 108: Introduction to Games Studies

In the dynamic world of video game development, a powerful revolution has been quietly transforming how interactive experiences are created. Independent game developers, or "indie" game creators, have emerged as innovative storytellers and design pioneers, challenging traditional gaming paradigms and offering players unique, personal experiences that transcend mainstream entertainment.

Unlike mainstream games developed by large corporations with multi-million dollar budgets, indie games are typically created by small teams or even individual developers driven by artistic vision rather than pure commercial interests. These creators prioritize innovative gameplay mechanics, compelling narratives, and unique aesthetic experiences over conventional market formulas. Platforms like Steam …

Quantum Visual Feature Encoding Revisited, Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill, Samee U. Khan, Khoa Luu

Computer Science and Computer Engineering Faculty Publications and Presentations

Although quantum machine learning has been introduced for a while, its applications in computer vision are still limited. This paper, therefore, revisits the quantum visual encoding strategies, the initial step in quantum machine learning. Investigating the root cause, we uncover that the existing quantum encoding design fails to ensure information preservation of the visual features after the encoding process, thus complicating the learning process of the quantum machine learning models. In particular, the problem, termed the “Quantum Information Gap” (QIG), leads to an information gap between classical and corresponding quantum features. We provide theoretical proof and practical examples with visualization …

Exploring The Content Of Introductory Quantitative Methods Courses For Education Doctoral Students, Samantha Brooke Patterson

Dissertations

Quantitative methods training is an integral part of an Education Doctoral Degree (EdD). Students tend to struggle with the content of these courses and consequently their quantitative proficiency has suffered. Currently, there is no consensus on the learning outcomes of introductory quantitative methods classes, leaving instructors to individually decide the content and teaching methods of their classes. The aim of this study was to capture the content of introductory quantitative methods course and determine their alignment with current best practices in statistics education.

• Q1 What curricular and pedagogical techniques are used in introductory quantitative methods course for EdD students?
• Q2 …

Does Mindset Matter: The Perceptions Pre-Licensure Nursing Students Have Regarding Mindset And Academic Success, Amanda Sue Schuster

Dissertations

Nursing programs need to graduate more students to increase the potential number of practicing nurses and help the nursing shortage. However, with high attrition rates, nursing programs are looking for ways to promote student success. Many factors lead to students not finishing a nursing program and nurse educators need to develop innovative ways to help students succeed. Identifying characteristics that make students successful is key to reducing attrition rates. One characteristic that a nurse educator can identify in students is a growth mindset. Mindset is formed by students’ beliefs and experiences, by having a growth mindset, one believes their intelligence …

2024 December - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

December was relatively warm and wet for West Tennessee, while areas further east were closer to average. The main weather and climate stories of December 2024 included the strong blast of cold air early in the month that led to widespread light snowfall and record cold temperatures from December 3-6, and two cold fronts that brought strong thunderstorms, localized flash flooding, some small hail, and strong winds to the state on December 18 and December 28-29. Heavy rains on the 29th led to flash flooding and closure of roads and temporary bridges in parts of Carter County that …

Magnetic Nano And Micro Rods As Tools For Characterizing Materials Mechanical Properties: Fundamentals And Applications, Artis Brasovs

All Dissertations

The focus of this dissertation is insect blood (Hemolymph). Hemolymph is analyzed by taking a materials science approach. Rheological characterization of hemolymph has been performed for the first time. Owing to a minute amount of available material, a new protocol was established where Magnetic Rotational Spectroscopy (MRS) with ferromagnetic nanorods was employed. The challenge was examining the microliter droplets' viscosity in less than a few minutes. This challenge was successfully resolved.

Blood is critical for the insect's survival: after wounding, the insect has to seal the wound quickly, in a few minutes. As the mechanism of fast clotting has never …

Computational Representation, Analysis And Verification Of Requirements In Engineering Design And Systems Engineering, Chandan Kumar Sahu

All Dissertations

Systems are developed to satisfy a set of requirements derived from stakeholders’ needs, defining the problem space for which the system is created as a feasible solution. The system design process begins with eliciting these requirements and concludes with validating whether the created system meets them. Requirements engineering (RE) encompasses elicitation, representation, analysis, documentation, verification, and validation. However, challenges in RE, such as imprecision in natural language (NL), proprietary restrictions, and a lack of standardized quality metrics, hinder the creation of well-formed and comprehensive requirements. These challenges complicate formalization and analysis of requirements.

This dissertation addresses these challenges by proposing …

Nanostructured Silicon Meta-Waveguides And Surfaces For Enhanced Light-Matter Interaction, Saddam Gafsi

All Dissertations

In this study, we tackle the challenge of light-matter interaction engineering and local field enhancement using various silicon photonic platforms based on three different approaches. (i) The first approach is based on boundary condition engineering where we present and show through simulation and experimental results, a silicon nanodisk “diabolo” configuration able to support significant local field enhancement levels in the range ~102 to 104 in the high index medium through proper structural modifications at the nanoscale. We show that the presented optical behavior is consistent with the anapole modes characterized by the observed near-field enhancement and coinciding with far-field suppression. …

"Don't Put Me Here To Meet A Quota": A Qualitative Descriptive Study Of Black Male Teacher Retention, Latresha Drummond

All Dissertations

The national teacher shortage has reached a fever pitch and can be accurately described as a crisis. Teacher vacancies in South Carolina (SC) have reached an all-time high since the Center for Educator Recruitment, Retention, and advancement began tracking the teacher shortage in 2001. Further, the phenomenon surrounding the exodus of Black teachers is understudied. Currently, no agency or organization tracks demographic turnover among the teacher workforce in South Carolina.

I utilized a qualitative descriptive design informed by an improvement science framework to identify motivating factors for teacher mobility among current and past Black male educators in SC public schools. …

Selective Hydroxyl Functionalization Using Novel Bifunctional Macrocyclic Catalysts And Sufex-Based Methodologies, Austin Seilkop

All Dissertations

The research behind this dissertation explores innovative strategies for the functionalization of alcohols. Alcohols are abundant in biologically relevant molecules and pharmaceutical drugs, so designing new methods for modifying them has gained significant interest over the years. The first and second chapters of this dissertation focus on the selective functionalization of a particular class of alcohols, amino alcohols, a well-represented functional handle in biomolecules. The hydroxyl functionalization of amino alcohols often demands multiple synthetic steps. We developed a new class of macrocyclic catalysts to enable precise and efficient transformations of amino alcohols, advancing the scope and efficiency of amino alcohol …

Protocol Transformations Across Osi Network Stack Layers For Attack, Evasion, And Defense, Nathan Tusing

All Dissertations

Network endpoints frequently contend with errors and deviations within protocols. Many factors account for these deviations including noise, tampering, and algorithm implementations. Intermediate nodes are expected to modify instantiated protocols and not guarantee correctness. This ability to modify traffic enables all sides of network security to alter security and performance properties of protocols, and we define this intermediary modification of an instantiated protocol as a transformation. Protocol transformations traverse layers of the OSI reference model and changes a protocol's time series byte sequence. Within this thesis, we show that this framework applies to multiple domains and protocols. Common examples of …

Leveraging High-Frequency Water Quality Data And Machine Learning For Monitoring Harmful Algal Blooms, Ibrahim Busari

All Dissertations

Freshwater management is one of the most critical resources on the earth due to the plethora of water use and its limited availability. Increased algae proliferation is one of the significant problems of freshwater bodies that is triggered by nutrient enrichment and enabling conditions such as light and warm temperatures. This algal proliferation is toxic to the ecosystem through their biomass and potential toxin production that can cause hypoxic conditions and is often referred to as Harmful Algal Blooms (HABs). Current monitoring approaches include laboratory analysis of water samples to observe algal cells, monitoring of water quality parameters using water …

Academic Vocabulary Acquisition In A 3rd Grade Science Classroom: A Mixed-Methods Embedded Study, Nicole Langenhuizen

All Dissertations

With the acceptance of the Next Generation Science Standards, elementary-aged students are encouraged to develop the skills needed to communicate their thinking in science efficiently and effectively (NGSS, 2013). Since implementing these new standards in 2013, South Carolina has seen a decline in science standardized testing scores for grades 3-5. These results show that science and engineering skills support 67% of U.S. jobs today (National Science Foundation, 2021), and the current trend is that science and engineering skills are essential to students today and provide a rationale for exploring how teachers can help students develop the vocabulary necessary to communicate …